Examining nonlinearity in population inflow estimation using big data: An empirical comparison of explainable machine learning models

•Nationwide census block group (CBG)-level population inflow is examined.•A range of explainable machine learning models is empirically compared.•Pronounced nonlinearities, threshold effects, and interaction effects are documented.•Effects of outliers, feature dependency, and local heterogeneity on interpretation techniques are discussed.